Ondrej Krejcar

Ondrej Krejcar received the Ph.D. degree in technical cybernetics from the VSB—Technical University of Ostrava, Ostrava, Czech Republic, in 2008.,From 2016 to 2020, he was the Vice Dean of science and research with the Faculty of Informatics and Management, University of Hradec Kralove (UHK), Hradec Kralove, Czech Republic, where he is currently a Full Professor in systems engineering and informatics with the Center for Basic and Applied Research, Faculty of Informatics and Management, UHK, and a Research Fellow with the Malaysia–Japan International Institute of Technology, University Technology Malaysia, Kuala Lumpur, Malaysia. He has been a Vice Rector for science and creative activities with UHK since 2020, where he is also the Director of the Center for Basic and Applied Research. From 2014 to 2019, he was the Deputy Chairperson of Panel 7 (processing industry, robotics, and electrical engineering) of the Epsilon Program, Technological Agency of the Czech Republic. He has also been a Management Committee Member Substitute with the COST CA16226 Project since 2017. He has been the Vice Leader and a Management Committee Member at WG4 with the COST CA17136 Project since 2018. Since 2019, he has been the Chairperson of the Program Committee of the KAPPA Program, Technological Agency of the Czech Republic. He is a Regulator of the EEA/Norwegian Financial Mechanism in the Czech Republic for 2019–2024. Since 2020, he has been Chairperson of Panel 1 (computer, physical, and chemical sciences) of the ZETA Program, Technological Agency of the Czech Republic. His research interests include technical cybernetics, ubiquitous computing, control systems, smart sensors, wireless technology, biomedicine, image segmentation and recognition, biometrics, biotelemetric system architectures, including portable device architectures and wireless biosensors, and the development of applications for mobile/remote devices with the use of remote or embedded biomedical sensors. Dr. Krejcar is currently on the Editorial Board of the Multidisciplinary Digital Publishing Institute (MDPI) Sensors Impact Factor (IF) journal (Q1/Q2 at Journal Citation Reports (JCR)) and several other Emerging Sources Citation Index (ESCI)-indexed journals. In 2018, he was the 14th Top Peer Reviewer in Multidisciplinary in the World according to Publons. He received the Top Reviewer in the Global Peer Review Award from Publons in 2019. His h-index is 27 according to the Web of Science, with more than 3300 citations received in the Web of Science, where more than 160 IF journal articles are indexed in the JCR index (h-index 30 at SCOPUS with more than 4200 citations).

Publications

Answering Why and When?: A Systematic Literature Review of Application Scenarios and Evaluation for Immersive Data Visualization Analytics
Answering Why and When?: A Systematic Literature Review of Application Scenarios and Evaluation for Immersive Data Visualization Analytics
Najwa Ayuni Jamaludin, Farhan Mohamed, Vei Siang Chan, Mohd Shahrizal Sunar, Ali Selamat, Ondrej Krejcar, Andres Iglesias. © 2023. 29 pages.
Immersive analytics (IA) is a fast-growing research field that concerns improving and facilitating human sense making and data understanding through an immersive experience....
Detecting Phishing URLs With Word Embedding and Deep Learning
Detecting Phishing URLs With Word Embedding and Deep Learning
Ali Selamat, Nguyet Quang Do, Ondrej Krejcar. © 2023. 24 pages.
The past decade has witnessed the rapid development of natural language processing and machine learning in the phishing detection domain. However, there needs to be more research...
A Fog-Based Threat Detection for Telemetry Smart Medical Devices Using a Real-Time and Lightweight Incremental Learning Method
A Fog-Based Threat Detection for Telemetry Smart Medical Devices Using a Real-Time and Lightweight Incremental Learning Method
Ali Selamat, Shilan S. Hameed, Liza Abdul Latiff, Shukor A. Razak, Ondrej Krejcar, Marek Penhaker. © 2022. 19 pages.
Smart telemetry medical devices do not have sufficient security measures, making them weak against different attacks. Machine learning (ML) has been broadly used for cyber-attack...
Improve Imbalanced Multiclass Classification Based on Modified SMOTE and Feature Selection for Student Grade Prediction
Improve Imbalanced Multiclass Classification Based on Modified SMOTE and Feature Selection for Student Grade Prediction
Siti Dianah, Ali Selamat, Ondrej Krejcar. © 2022. 19 pages.
In higher education institutions (HEI), the ability to predict student grades as an early warning system is one of the important areas that gained attention to improve...